Function : Business Intelligence and Analytics

POSITION SUMMARY :

The Data Scientist/ AI Engineer will build, and scale Generative AI solutions powered by LLMs and agentic workflows in a fast- paced environment. This role owns the end- to- end development of AI features-from prompt engineering and retrieval- augmented generation (RAG) to autonomous agents deployed in production. The AI Engineer works closely with founders, product, and engineering teams to rapidly turn ideas into production- ready GenAI solutions that deliver measurable business impact.

KEY ACCOUNTABILITIES/ KEY RESPONSIBILITIES :

- Build and deploy Generative AI applications using LLMs, including chat, summarization, reasoning, and content generation

- Design and implement agentic AI systems with tool calling, planning, memory, and multi- step workflows

- Develop RAG pipelines using embeddings, vector databases, and retrieval strategies

- Own the full GenAI lifecycle : prompt engineering, fine- tuning, evaluation, deployment, and monitoring

- Optimize GenAI systems for accuracy, cost, latency, and scalability

- Collaborate with product and engineering teams to rapidly ship AI features

- Document system behaviour, limitations, and best practices

DESIRED PROFILE :

Qualifications and Skills :

- Bachelor's degree in Statistics, Economics, Finance, Mathematics,Computers or a related quantitative field

- Engineering / MBA background from a premier institute is preferred.

- Minimum 3+ years' experience

- Strong proficiency in Python, cloud hyper scalars, MLOps, DevsecOps

- Hands- on experience with LLMs, GenAI, or agentic AI systems, experience with agent frameworks

- Solid understanding of RAG, embeddings, and transformer- based models,

- Exposure to fine- tuning, LLM evaluation, or guardrail

- Experience deploying AI solutions to production environments

- Ability to thrive in ambiguity and take end- to- end ownership